using System;
using System.Collections.Generic;
using UnityEngine;

// A* needs only a WeightedGraph and a Vector3 type L, and does *not*
// have to be a grid. However, in the example code I am using a grid.





public class SquareGrid
{
    // Implementation notes: I made the fields public for convenience,
    // but in a real project you'll probably want to follow standard
    // style and make them private.

    public static readonly Vector3[] DIRS = new[]
        {
            new Vector3(1,0, 0),
            new Vector3(1,0, 1),
            new Vector3(1,0, -1),
            new Vector3(-1,0, 1),
            new Vector3(-1,0, -1),
            new Vector3(0,0, -1),
            new Vector3(-1,0, 0),
            new Vector3(0,0, 1)
        };

    public int width, height;
    //public HashSet<NodeElement> walls = new HashSet<NodeElement>();
    //public HashSet<NodeElement> forests = new HashSet<NodeElement>();
    public NodeElement[,] nodes;
    public SquareGrid(int width, int height)
    {
        nodes = new NodeElement[width, height];
        for (int x = 0; x < width; x++)
        {
            for (int y = 0; y < height; y++)
            {
                //nodes[x, y].item1 = new Vector3(x, 0, y);
                //nodes[x, y].item2 = 1;
                //nodes[x, y].passable = true;
                nodes[x, y] = new NodeElement(new Vector3(x, 0, y), 1, true);
            }
        }
        this.width = width;
        this.height = height;
    }
    public NodeElement FindNode(int x, int y)
    {
        if (InBounds(x, y))
            return nodes[x, y];
        return null;
    }
    public bool InBounds(NodeElement id)
    {
        return 0 <= id.item1.x && id.item1.x < width
            && 0 <= id.item1.z && id.item1.z < height;
    }
    public bool InBounds(int x, int y)
    {
        return 0 < x && x < width
            && 0 <= y && y < height;
    }
    public bool Passable(NodeElement id)
    {
        return id.passable && id.occupied == false;//!walls.Contains(id);
    }

    public double Cost(NodeElement b)
    {
        return b.item2;//forests.Contains(b) ? 5 : 1;
    }

    public IEnumerable<NodeElement> Neighbors(NodeElement id)
    {
        foreach (var dir in DIRS)
        {
            int x = (int)(id.item1.x + dir.x);
            int y = (int)(id.item1.z + dir.z);
            if (InBounds(x, y))
            {
                NodeElement next = FindNode(x, y);
                if (Passable(next))
                {
                    yield return next;
                }
            }
        }
    }
}

public class NodeElement
{
    public Vector3 item1;
    public double item2;
    public bool passable;
    public Seeker occupied;
    public NodeElement(Vector3 _node, double _double, bool _passable)
    {
        item1 = _node;
        item2 = _double;
        passable = _passable;
        occupied = null;
    }
    public NodeElement()
    {
        item1 = Vector3.zero;
        item2 = 0;
        passable = false;
        occupied = null;
    }
}
public class PriorityQueue
{
    // I'm using an unsorted array for this example, but ideally this
    // would be a binary heap. Find a binary heap class:
    // * https://bitbucket.org/BlueRaja/high-speed-priority-queue-for-c/wiki/Home
    // * http://visualstudiomagazine.com/articles/2012/11/01/priority-queues-with-c.aspx
    // * http://xfleury.github.io/graphsearch.html
    // * http://stackoverflow.com/questions/102398/priority-queue-in-net
    private List<NodeElement> elements = new List<NodeElement>();

    public int Count
    {
        get { return elements.Count; }
    }

    public void Enqueue(Vector3 item, double priority, bool passable)
    {
        elements.Add(new NodeElement(item, priority, passable));
    }
    public void Enqueue(NodeElement next)
    {
        elements.Add(next);
    }
    public NodeElement Dequeue()
    {
        int bestIndex = 0;

        for (int i = 0; i < elements.Count; i++)
        {
            if (elements[i].item2 < elements[bestIndex].item2)
            {
                bestIndex = i;
            }
        }
        NodeElement bestItem = elements[bestIndex];
        elements.RemoveAt(bestIndex);
        return bestItem;
    }

}


/* NOTE about types: in the main article, in the Python code I just
 * use numbers for costs, heuristics, and priorities. In the C++ code
 * I use a typedef for this, because you might want int or double or
 * another type. In this C# code I use double for costs, heuristics,
 * and priorities. You can use an int if you know your values are
 * always integers, and you can use a smaller size number if you know
 * the values are always small. */

public class AStarSearch
{
    public Dictionary<NodeElement, NodeElement> cameFrom
        = new Dictionary<NodeElement, NodeElement>();
    public Dictionary<NodeElement, double> costSoFar
        = new Dictionary<NodeElement, double>();

    // Note: a generic version of A* would abstract over Vector3 and
    // also Heuristic
    static public double Heuristic(Vector3 a, Vector3 b)
    {
        return Math.Abs(a.x - b.x) + Math.Abs(a.y - b.y);
    }
    NodeElement _start, _goal;
    public AStarSearch(SquareGrid graph, NodeElement start, NodeElement goal)
    {
        var frontier = new PriorityQueue();
        frontier.Enqueue(start);
        _start = start;
        _goal = goal;
        cameFrom[start] = start;
        costSoFar[start] = 0;

        while (frontier.Count > 0)
        {
            NodeElement current = frontier.Dequeue();

            if (current.Equals(goal))
            {
                break;
            }

            foreach (var next in graph.Neighbors(current))
            {
                double newCost = costSoFar[current]
                    + graph.Cost(next);
                if (!costSoFar.ContainsKey(next)
                    || newCost < costSoFar[next])
                {
                    costSoFar[next] = newCost;
                    double priority = newCost + Heuristic(next.item1, goal.item1);
                    frontier.Enqueue(next);
                    cameFrom[next] = current;
                }
            }
        }
    }

    public List<NodeElement> FindShortestPath()
    {
        NodeElement next = _goal;
        List<NodeElement> path = new List<NodeElement>();
        path.Add(next);
        if (cameFrom.ContainsKey(next))
        {
            for (int i = 0; i < cameFrom.Count; ++i)
            {
                next = cameFrom[next];
                path.Add(next);
                if (next == _start)
                {
                    path.Reverse();
                    break;
                }
            }
        }
        return path;
    }
}